Syllabus

Click on the date for more information about each lecture

Detailed version of the full syllabus is available here

Date	Topic	Reading
9/25	Introduction: The concept and biology of brain connectivity Learning Objectives: After this lecture, you should be able to: * Describe the different ways in which the concept of “brain connectivity” can be defined * Describe the structural and functional basis of brain connectivity	Required: - Brain connectivity - From Cajal to Connectome and Beyond
9/27	Hands on: Visualizing white matter structure with FSLeyes and nilearn Learning Objectives: After this lecture, you should be able to: * Identify major white matter tracts in probabilistic atlases * Load and visualize tract atlases in both FSLeyes and Python
10/2	Graph theory Learning Objectives: After this lecture, you should be able to: * Describe the basic concepts of graph theory	Required: - Network Science (Sections 1-4 and 7)
10/4	Hands on: Graph theory Learning Objectives: After this lecture, you should be able to: * Use NetworkX to create and analyze graph data
10/9	Network modeling Learning Objectives: After this lecture, you should be able to: * Describe the concepts of integration and segregation * Describe the concept of modularity * Describe the concept of community detection and the different approaches	Required: - Complex network measures of brain connectivity: uses and interpretations Further reading: - Community detection in graphs - Clustering: Science or Art?
10/11	Hands on: Network modeling
10/16	Micro/nanoscale connectomics	Required: - Micro-connectomics: probing the organization of neuronal networks at the cellular scale - Saturated Reconstruction of a Volume of Neocortex
10/18	Stand-up for paper proposals - each student presents a short overview of their project idea for discussion and feedback
10/23	Tract tracing	- A mesoscale connectome of the mouse brain - Classic and Contemporary Neural Tract-Tracing Techniques
10/25	Hands on: Tract-tracing data	- A Weighted and Directed Interareal Connectivity Matrix for Macaque Cerebral Cortex
10/30	Diffusion MRI	- Using diffusion imaging to study human connectional anatomy - Limits to anatomical accuracy of diffusion tractography using modern approaches
11/1	Hands on: Diffusion MRI analysis with dipy (Chris Gorgolewski, Guest lecturer)	TBD
11/6	Resting fMRI	- Precision functional mapping of individual human brains - Studying brain organization via spontaneous fMRI signal
11/8	Hands on: Resting fMRI analysis
11/13	Task fMRI	- Six problems for causal inference from fMRI - Tools of the trade: psychophysiological interactions and functional connectivity
11/15	Hands on: Network modeling with fMRI data	- Network modelling methods for fMRI
11/27	Large-scale brain networks	- The organization of the human cerebral cortex estimated by intrinsic functional connectivity - Large-Scale Gradients in Human Cortical Organization
11/29	Hands on: Parcellation and large-scale networks
12/4	Dynamics of brain networks	-Resting brains never rest: computational insights into potential cognitive architectures -Criticality in the brain: A synthesis of neurobiology, models and cognition
12/6	Hands on: Simulating dynamics using the Virtual Brain	TBD
12/10	Final meeting with project presentations, 12:15-3:15 pm